This paper applies the Evolutionary Strategy (ES) metaheuristic to the automatic test data generation problem. The problem consists in creating automatically a set of input data to test a program. This is a required step in software development and a time consuming task in all software companies. We describe our proposal and study the influence of some parameters of the algorithm in the results...

This article proposes a novel approach to quantitative software reliability assessment ensuring high interplay coverage for software components and decentralized (sub-)systems. The generation of adequate test cases is based on the measurement of their operational representativeness, stochastic independence and interaction coverage. The underlying multi-objective optimization problem is solved b...

for the performance improvement and higher flexibility in irrigation networks, applications of automatic systems are expanding and on evaluation of their success for achieving the objectives are essential and necessary. considering various equipment, algorithms, and their applications at different levels of irrigation networks, the performance of automatic systems is a function of the performan...

We report on GADGET, a new software test generation system that uses combinatorial optimization to obtain condition/decision coverage of C/C++ programs. The GADGET system is fully automatic and supports all C/C++ language constructs. This allows us to generate tests for larger programs than those previously reported in the literature. We address a number of issues that are encountered when auto...

In this paper we have explained automatic test data generation particularly for class testing of object oriented programming. During test data generation we have implemented the Genetic program Fuzzy logic control auxiliary hybridization techniques. Some cases genetic algorithm has been used for optimized the desired results. As a future challenges we have made comments on the utilization of th...